• Journal of Korean Society of Transportation
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• v.30 no.3
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• pp.71-82
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• 2012

This study analyzed factors affecting daily travel times at each stage of commuters' life cycle. In this study, travel times were dealt with in the context of trip chain. That is, the travel time was defined as the total amount of time commuters had spent to move for daily activities from leaving to coming back home. A commuter's life cycle was divided into 6 stages on a basis of both householder's age and family type: i.e., the unmarried youth period, the family forming period, the children education period, the children youth period, the children independence period, and the aged period. Variables such as commuting times, home-based trip cycle recurrences, and the number of stops differed for each stage of life cycle, the latter of which represents how many places a commuter dropped by during a trip cycle. Several factors were found to affect commuting times at each stage of life cycle as a result of applying a Cox proportional hazard model. The empirical study was conducted using 2010' household travel survey data collected from Gyeonggi-do.

• Korea journal of population studies
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• v.29 no.3
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• pp.159-188
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• 2006

This study attempts to create a longitudinal dataset by linking tdata on the identical individuals across the monthly sample household management lists of the Economically Active Population Survey(EAPS) and the Household Income and Expenditure Survey(HIES). Using the data constructed through such process, the study also tryies to analyze the duration of longitudinal responses and the characteristics of nonrespondents. Between 1998 and 2002, longitudinal response rates had declined to 46% of total EAPS and 34% of total HIES. The fact that nonresponse was not a random phenomenon leads to concerns about the representativeness of the remaining sample. Using Cox's proportional hazard model the study revealed that the duration of longitudinal responses is affected by the ownership of house and the age of the respondent.

• Journal of Preventive Medicine and Public Health
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• v.45 no.1
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• pp.14-20
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• 2012

Objectives: The aim of this study was to evaluate and quantify the risk of both individual and combined health behaviors on premature mortality in middle aged men in Korea. Methods: In total, 14 533 male subjects 40 to 59 years of age were recruited. At enrollment, subjects completed a baseline questionnaire, which included information about socio-demographic factors, past medical history, and life style. During the follow-up period from 1993 to 2008, we identified 990 all-cause premature deaths using national death certificates. A Cox proportional hazard regression model was used to estimate the hazard ratio (HR) of each health risk behavior, which included smoking, drinking, physical inactivity, and lack of sleep hours. Using the Cox model, each health behavior was assigned a risk score proportional to its regression coefficient value. Health risk scores were calculated for each patient and the HR of all-cause premature mortality was calculated according to risk score. Results: Current smoking and drinking, high body mass index, less sleep hours, and less education were significantly associated with all-cause premature mortality, while regular exercise was associated with a reduced risk. When combined by health risk score, there was a strong trend for increased mortality risk with increased score (p-trend < 0.01). When compared with the 1-9 score group, HRs of the 10-19 and 20-28 score groups were 2.58 (95% confidence intervals [CIs], 2.19 to 3.03) and 7.09 (95% CIs, 5.21 to 9.66), respectively. Conclusions: Modifiable risk factors, such as smoking, drinking, and regular exercise, have considerable impact on premature mortality and should be assessed in combination.

• The Journal of the Korea Contents Association
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• v.19 no.5
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• pp.287-295
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• 2019

This study was conducted to analyze firm survival rate and impact factors of survival of Foreign-invested Companies in Korea which is between 2006 and 2017. An empirical analysis of the survival factors of firms used explanatory variables such as characteristics of the and 3 firm dummy and 2 firm factors, financial variables of 3 profitability and 3 stability factors. The Kaplan-Meier method was chosen to perform analyses on the survival rates, Cox Proportional Hazard Model took to conduct on the impact factors. As a result of the impact factors of Foreign-invested Companies survival, Ownership (OS), Labour (NE ) of characteristics of the firm had positive effects. The Gross Sales Profit (GSP), Net Profit (NP ) and Operating Profit (OP ) of the financial characteristics had a positive effect. Additional Asset (LA ) had positive effects and Capital (LC), Debt (LB ) had a negative effect. Other factors did not produce significant results.

• The Journal of the Korea Contents Association
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• v.22 no.6
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• pp.692-700
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• 2022

This study was conducted to analyze firms' death rate and impact factors on the death of Foreign-invested Companies in Korea which is between 20013 and 2017. Cox Proportional Hazard Model took to conduct on the death impact factors, such as 2 characteristics factors of the firm, and 4 financial characteristics variables, variables, and 4 profitability factors. As a result of the impact factors of Foreign-invested Companies' death the Labour(NE) variables of characteristics firm had negative effects. And the Debt(LB), Operating Profit (OP), and Sales Profit (SP) of the financial characteristics had a negative effect. Other factors did not produce significant results. As a result of an empirically comparative analysis of the mortality rate of foreign-invested companies by the Kaplan-Meier method, it was analyzed that fully owned companies and large enterprises had lower extinction risk and greater sustainable management potential than joint ventures or SMEs.

• The Journal of Industrial Distribution & Business
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• v.9 no.7
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• pp.43-52
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• 2018

Purpose - The main purpose of this paper is to examine the effect of children's age on maternal labor supply in Korea using survival analysis. Specifically, we focus on the career re-interruption of women having children under age 12, which has rarely been studied in the existing literature. Research design, data, and methodology - We use micro data from the Korea Labor and Income Panel Study (KLIPS) surveyed from 1998 to 2016. Instead of using a pre-school child dummy or the number of young children as an explanatory variable, 9 children's age dummies are included to capture the effect of nurturing 0 to 9 years old children. This study estimates the hazard of a woman's exiting the labor market after her first experience of the career interruption, rather than the hazard of the first career interruption itself. A Cox proportional hazard model is applied to numerically capture the impact of children's age on behavioral changes in maternal labor supply. The sample used in this analysis is women between 15 and 54 years old. Most of all, we restrict the sample to women who had at least a child between 0 and 12 years old at the time of quitting their jobs. Results - The Cox proportional hazard model estimates show a strong negative effect of a 0-year-old child on maternal labor supply. Mothers with newborns have a high hazard ratio of labor force exit after the re-entry. The hazard of women with infants is three times higher than those with children aged 10 to 18. Additionally, the results show that not only newborns, but also children in the age of school-entry have a negative impact on their mother's labor supply. Conclusions - The findings reveal that children's ages need to be properly expanded and included when analyzing the effect of children and their ages on married women's labor supply, especially on women's career re-interruption. A large negative effect of 7-year-old children on maternal labor supply found here indicates that supporting mothers with school age children as well as pre-school children is necessary to prevent mothers from leaving the labor market.

• 한국노년학
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• v.31 no.2
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• pp.259-276
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• 2011

If frail elderly could use home care services adequately, quality of their life might improve and their costs of service would be decreased. The purpose of this study is to examine the factors on institutionalization of elderly using home care services in Korean long-term care insurance system. This study used the data of '2009 satisfaction survey of Korean long-term care system'. The survey proceeded using sampling data by region, level of long-term care need, and insurance type among beneficiaries from August 2009 to September 2010. The onset dates of institutionalization of 1,230 participants were ascertained from long-term care insurance claim data. This study calculated hazard ratio through Cox Proportional Hazard Model. The results showed that if elderly using home care services suffer a fracture, the hazard ratio of institutionalization is higher significantly. Although not significant, if older persons have more items of damaged cognitive functions, the hazard ratio of institutionalization is higher. The results have policy implications to supplement of home care service system and postpone institutionalization of elderly.

• Proceedings of the Korean Statistical Society Conference
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• 2005.05a
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• pp.17-23
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• 2005

In this paper we consider the well-known semiparametric proportional hazards models for survival analysis. These models are usually used with few covariates and many observations (subjects). But, for a typical setting of gene expression data from DNA microarray, we need to consider the case where the number of covariates p exceeds the number of samples n. For a given vector of response values which are times to event (death or censored times) and p gene expressions(covariates), we address the issue of how to reduce the dimension by selecting the significant genes. This approach enables us to estimate the survival curve when n ${\ll}$p. In our approach, rather than fixing the number of selected genes, we will assign a prior distribution to this number. The approach creates additional flexibility by allowing the imposition of constraints, such as bounding the dimension via a prior, which in effect works as a penalty To implement our methodology, we use a Markov Chain Monte Carlo (MCMC) method. We demonstrate the use of the methodology to diffuse large B-cell lymphoma (DLBCL) complementary DNA (cDNA) data and Breast Carcinomas data.

• Korean Journal of Adult Nursing
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• v.29 no.1
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• pp.98-107
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• 2017

Purpose: The purpose of this study was to investigate the effect of geriatric syndrome on mortality among community-dwelling older adults in Korea. Methods: Data were obtained from the Actual Living Condition of the Elderly and Welfare Need Survey, with a baseline study in 2008 and a 3-year follow-up of mortality data. The mortality risk was measured using the hierarchical Cox proportional hazard model. Results: In Cox regression analysis, male (Hazard Ratio [HR], 2.53; 95% Confidence Interval [CI], 2.12~3.01), old age (HR, 2.14; 95% CI, 1.82~2.53), low education level (HR, 1.31; 95% CI, 1.04~1.65), limitation in instrumental activities of daily living (HR, 1.91; 95% CI, 1.60~2.28), depressive symptoms (HR, 1.21; 95% CI, 1.01~1.43), and frailty (HR, 2.32; 95% CI, 1.78~3.03) significantly affected mortality risk. Conclusion: Based on the results of this study, nursing intervention programs should be provided to decrease preventable death in older adults.

• Journal of Hospice and Palliative Care
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• v.5 no.2
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• pp.111-124
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• 2002

Purpose : Although the average life expectancy has increased due to advances in medicine, mortality due to cancer is on an increasing trend. Consequently, the number of terminally ill cancer patients is also on the rise. Predicting the survival period is an important issue in the treatment of terminally ill cancer patients since the choice of treatment would vary significantly by the patents, their families, and physicians according to the expected survival. Therefore, we investigated the prognostic factors for increased mortality risk in terminally ill cancer patients to help treat these patients by predicting the survival period. Methods : We investigated 31 clinical parameters in 157 terminally ill cancer patients admitted to in the Department of Family Medicine, National Health Insurance Corporation Ilsan Hospital between July 1, 2000 and August 31, 2001. We confirmed the patients' survival as of October 31, 2001 based on medical records and personal data. The survival rates and median survival times were estimated by the Kaplan-Meier method and Log-rank test was used to compare the differences between the survival rates according to each clinical parameter. Cox's proportional hazard model was used to determine the most predictive subset from the prognostic factors among many clinical parameters which affect the risk of death. We predicted the mean, median, the first quartile value and third quartile value of the expected lifetimes by Weibull proportional hazard regression model. Results : Out of 157 patients, 79 were male (50.3%). The mean age was $65.1{\pm}13.0$ years in males and was $64.3{\pm}13.7$ years in females. The most prevalent cancer was gastric cancer (36 patients, 22.9%), followed by lung cancer (27, 17.2%), and cervical cancer (20, 12.7%). The survival time decreased with to the following factors; mental change, anorexia, hypotension, poor performance status, leukocytosis, neutrophilia, elevated serum creatinine level, hypoalbuminemia, hyperbilirubinemia, elevated SGPT, prolonged prothrombin time (PT), prolonged activated partial thromboplastin time (aPTT), hyponatremia, and hyperkalemia. Among these factors, poor performance status, neutrophilia, prolonged PT and aPTT were significant prognostic factors of death risk in these patients according to the results of Cox's proportional hazard model. We predicted that the median life expectancy was 3.0 days when all of the above 4 factors were present, $5.7{\sim}8.2$ days when 3 of these 4 factors were present, $11.4{\sim}20.0$ days when 2 of the 4 were present, and $27.9{\sim}40.0$ when 1 of the 4 was present, and 77 days when none of these 4 factors were present. Conclusions : In terminally ill cancer patients, we found that the prognostic factors related to reduced survival time were poor performance status, neutrophilia, prolonged PT and prolonged am. The four prognostic factors enabled the prediction of life expectancy in terminally ill cancer patients.